Trastornos respiratorios del sueño en Insuficiencia Cardíaca con fracción de eyección reducida

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Introduction: Sleep-disordered breathing (SDB) are highly prevalent in patients with heart failure (HF). The presence of obstructive sleep apnea syndrome (OSA) determines a worse prognosis in these patients. There are questionnaires aimed at evaluating the probability of OSA, although none have been validated in patients with HF. The primary objective of this study was to establish the prevalence of SDB in a cohort of patients with HF and reduced ejection fraction (HFrEF) from the Multidisciplinary HF Unit (UMIC). As a secondary objective, to evaluate the usefulness of the Stop-Bang, Berlin, and 2ABN3M questionnaires for TRS screening in these patients. Methodology: Cross-sectional, observational study, including the active cohort of the UMIC, over 18 years with HFrEF, clinically stable and informed consent. Patients with cognitive, neurological or hearing impairment with limitations when conducting the interview were excluded. Patients with other limiting or uncontrolled sleep disorders, continuous home oxygen therapy requirements, did not enter the study. Berlin, Stop-Bang, and 2ABN3M questionnaires were administered, classifying the population into high-risk, intermediate-risk, and low-risk groups of presenting SDB. All patients underwent outpatient respiratory polygraphy (RP). Descriptive statistics were used to characterize demographic variables, measures of central tendency and dispersion. SPSS statistical software was used. Results: 387 patients were included, 248 men (64.1%), mean age was 63.5 ± 0.6 years. The etiology of HF was ischemic in 41.6% of patients. The body mass index was 29.3 ± 0.3 kg/m2. LVEF was 34.2 ± 0.5, pro-BNP 1233.8 ± 137.6 pg/ml. The results of the questionnaires showed that 52.1% (198) presented a high risk of SDB according to the Berlin questionnaire. With Stop-Bang, 35.9% (139) were high risk, 42.1% (163) intermediate risk, and the remaining 22% (85) low risk. With the 2ABN3M score, 62% (240) were high risk. A total of 156 respiratory polygraphs (40.3% of the population) were performed. The cut-off point to define the presence of sleep apnea was considered to be an AHI >15. 58.3% (91) of the patients presented TRS. Of these, 95% presented obstructive apnea and 5% central apnea with periodic Cheyne-Stokes breathing. A high percentage (26%) presented AHI greater than 30. The sensitivity of the Berlin and Stop-Bang questionnaires was 75.8% and 91.2%, respectively, with a specificity of 53.8% and 24.6%. Regarding the 2ABN3M score, a sensitivity of 71.4% and a specificity of 44.6% were observed. Conclusions: The prevalence of sleep-disordered breathing in patients with HFrEF was high in our cohort and obstructive apnea predominated. Given the high sensitivity (91.2%) of the Stop-Bang questionnaire found in our study, it could be useful as a screening tool for TRS in this type of patient. The importance of investigating this pathology whose clinical presentation can be non-specific and remain underdiagnosed is highlighted.

Introdução: Os distúrbios respiratórios do sono (DRS) são altamente prevalentes em pacientes com insuficiência cardíaca (IC). A presença da síndrome da apneia obstrutiva do sono (SAOS) determina pior prognóstico nesses pacientes. Existem questionários destinados a avaliar a probabilidade de AOS, porém nenhum foi validado em pacientes com IC. O objetivo primário deste estudo foi estabelecer a prevalência de DRS em uma coorte de pacientes com IC e fração de ejeção reduzida (ICFEr) da Unidade Multidisciplinar de IC (UMIC). Como objetivo secundário, avaliar a utilidade dos questionários Stop-Bang, Berlin e 2ABN3M para triagem de SRT nesses pacientes. Metodologia: Estudo transversal, observacional, inclui a coorte ativa da UMIC, maiores de 18 anos com ICFEr, clinicamente estável e consentimento informado. Foram excluídos pacientes com deficiência cognitiva, neurológica ou auditiva com limitações na realização da entrevista. Pacientes com outros distúrbios do sono limitantes ou descontrolados, requisitos de oxigenoterapia domiciliar contínua, não entraram no estudo. Os questionários Berlin, Stop-Bang e 2ABN3M foram aplicados, classificando a população em grupos de alto risco, risco intermediário e baixo risco de apresentar DRS. Todos os pacientes foram submetidos à poligrafia respiratória (PR) ambulatorial. A estatística descritiva foi utilizada para caracterizar as variáveis ​​demográficas, medidas de tendência central e dispersão. Foi utilizado o software estatístico SPSS. Resultados: foram incluídos 387 pacientes, 248 homens (64,1%), com idade média de 63,5 ± 0,6 anos. A etiologia da IC foi isquêmica em 41,6% dos pacientes. O índice de massa corporal foi de 29,3 ± 0,3 kg/m2. FEVE foi de 34,2 ± 0,5, pro-BNP 1233,8 ± 137,6 pg/ml. Os resultados dos questionários mostraram que 52,1% (198) apresentaram alto risco de DRS de acordo com o questionário de Berlim. Com Stop-Bang, 35,9% (139) eram de alto risco, 42,1% (163) de risco intermediário e os restantes 22% (85) de baixo risco. Com a pontuação 2ABN3M, 62% (240) eram de alto risco. Foram realizados 156 polígrafos respiratórios (40,3% da população). O ponto de corte para definir a presença de apneia do sono foi considerado um IAH >15. 58,3% (91) dos pacientes apresentaram SRT. Destes, 95% apresentavam apnéia obstrutiva e 5% apnéia central com respiração Cheyne-Stokes periódica. Uma alta porcentagem (26%) apresentou IAH maior que 30. A sensibilidade dos questionários Berlin e Stop-Bang foi de 75,8% e 91,2%, respectivamente, com especificidade de 53,8% e 24,6%. Em relação ao escore 2ABN3M, observou-se sensibilidade de 71,4% e especificidade de 44,6%. Conclusões: A prevalência de distúrbios respiratórios do sono em pacientes com ICFEr foi alta em nossa coorte, com predominância de apneias obstrutivas. Dada a alta sensibilidade (91,2%) do questionário Stop-Bang encontrado em nosso estudo, ele pode ser útil como uma ferramenta de triagem para ERT nesse tipo de paciente. Ressalta-se a importância da investigação dessa patologia cuja apresentação clínica pode ser inespecífica e permanecer subdiagnosticada.

Obstructive sleep apnea in surgical patients and its relationship with difficult intubation: two years of experience from a single center

Abstract Background and objectives: In this study, we aimed to determine the risk of obstructive sleep apnea (OSA) in patients undergoing elective surgery and its relationship with difficult intubation (DI). Methods: This prospective, descriptive, cross-sectional study was conducted between December 2018 and February 2020 in the anesthesiology and reanimation service of a training and research hospital. The study included patients who were ASA I-II, 18 years of age, and older who underwent elective surgery under general anesthesia. A form regarding the baseline characteristics of the participants as well as STOP-Bang score, Mallampati, and Cormack-Lehane classification was used to collect the data. Results: The study included 307 patients. It was determined that 64.2% of patients had a high risk of OSA. The presence of DI (determined by repeated attempts at intubation) was 28.6% in the high-risk OSA group, while there was no DI in the low-risk OSA group. A statistically significant difference was found between the groups in terms of OSA risk according to the presence of DI according to repeated attempts, Cormack-Lehane classification, and Mallampati classification (p < 0.001). Conclusion: Due to the high rate of DI in patients with a high risk of OSA, the security of the airway in these patients is endangered. Early clinical recognition of OSA can help in designing a safer care plan.

Establishment and evaluation of a risk prediction model for severe obstructive sleep apnea / 西安交通大学学报(医学版)

【Objective】 To construct a prediction model of severe obstructive sleep apnea (OSA) risk in the general population by using nomogram in order to explore the independent risk factors of severe OSA and guide the early diagnosis and treatment. 【Methods】 We retrospectively enrolled patients who had been diagnosed by polysomnography and divided them into training and validation sets at the ratio of 7∶3. Patients were divided into severe OSA group and non-severe OSA group according to apnea hypopnea index (AHI)>30. Variables entering the model were identified by least absolute shrinkage and selection operator regression model (Lasso), and logistic regression (LR) method. Then, multivariable logistic regression analysis was used to establish the nomogram, and the area under the receiver operating characteristic curve (AUC) was used to evaluate the discriminative properties of the nomogram model. Finally, we conducted decision curve analysis (DCA) of nomogram model, STOP-Bang questionnaire and Berlin questionnaire to assess clinical utility. 【Results】 Through single factor and multiple factor logistic regression analyses, the independent risk factors for severe OSA were screened out, including moderate and severe sleepiness, family history of hypertension, history of smoking, drinking, snoring, history of suffocation, sedentary lifestyle, male, age, body mass index (BMI), waist and neck circumference. Lasso logistic regression identified smoke, suffocation time, snoring time, waistline, Epworth sleepiness scale (ESS) and BMI as predictive factors for inclusion in the nomogram. The AUC of the model was 0.795 [95% confidence interval (CI): 0.769-0.820] . Hosmer-Lemeshow test indicated that the model was well calibrated (χ2=3.942, P=0.862). The DCA results on the visual basis confirmed that the nomogram had superior overall net benefits within a wide, practical threshold probability range which displayed the nomogram was higher than that of STOP-Bang questionnaire and Berlin questionnaire, which is clinically useful. The Clinical Impact Curve (CIC) analysis showed the clinical effectiveness of the prediction model when the threshold probability was greater than 82% of the predicted score probability value. The prediction model determined that the high-risk population with severe OSA was highly matched with the actual population with severe OSA, which confirmed the high clinical effectiveness of the prediction model. 【Conclusion】 The model performed better than STOP-Bang questionnaire and Berlin questionnaire in predicting severe OSA and can be applied to screening. And it can be helpful to the early diagnosis and treatment of OSA in order to reduce social burden.

Evaluación de riesgo de apnea obstructiva del sueño y de la adherencia al tratamiento farmacológico en pacientes con hipertensión arterial / Risk assessment of obstructive sleep apnea and adherence to pharmacological treatment in patients with arterial hypertension

Introducción:existe una sospecha sobre la relación bidireccional entre la apnea obstructiva del sueño (AOS) y la hipertensión arterial (HTA). Ambas ejercen una acción sinérgica sobre desenlaces cardiovasculares porlo quees trascendente ponderar la prevalencia de riesgo para AOS en los hipertensos. En este último grupo también hemos investigado la tasa de adherencia a los fármacos prescritos. Metodología:mediante un estudio de casos y controles y con la aplicación del cuestionario STOP-BANG se han discriminado las categorías de riesgo para apnea de sueño en las dos cohortes. Para el análisis de la adherencia a fármacos antihipertensivos se utilizó el cuestionario abreviado de Morisky. Resultados:se incluyeron a 590 individuos (295 casos y 295 controles. Se observó alto riesgo para AOS en el grupo de hipertensos (36,6%) comparado con el 14,2% del grupo control. Por otro lado, el sexo masculino OR 7,77 (IC95% 4,33-13,84), la obesidad OR 5,03 (IC95% 3,11-8,13) y la HTA OR 4,31 (IC95% 2,64-7,03) se ponderan significativos en un modelo de ajuste logístico aquí estudiado. El 61,69% de los hipertensos refería adherencia al tratamiento farmacológico prescrito. Discusión:el tamizaje de AOS es factible con un cuestionario aplicable en la práctica clínica diaria. De la probabilidad clínica pre-test hay que partir hacia métodos diagnósticos específicos para el diagnóstico de AOS, enfatizando casos de HTA resistente, HTA nocturna y HTA enmascarada. Se deberían realizar estudios locales que nos ayuden a comprender las causas de la falta de adherencia a fármacos antihipertensivos en una fracción importante de los individuos con HTA

Introduction:there is a suspicion about the bidirectional relationship between obstructive sleep apnea (OSA) and arterial hypertension (AHT). Both have a synergistic action on cardiovascular outcomes, so it is important to assess the prevalence of risk for OSA in hypertensive patients. In this last group we have also investigated the rate of adherence to prescribed drugs.Metodology:through a case-control study and with the application of the STOP-BANG questionnaire, the risk categories for sleep apnea in the two cohorts have been discriminated. For the analysis of adherence to antihypertensive drugs, the abbreviated Morisky questionnaire was used. Results:590 individuals were included (295 cases and 295 controls. A high risk for OSA was observed in the hypertensive group (36.6%) compared to 14.2% in the control group. On the other hand, the male sex OR 7.77 (95%CI 4.33-13.84), obesity OR 5.03 (95%CI 3.11-8.13) and hypertensionOR4.31(95%CI 2.64-7.03) they areweighted significant in a logistic adjustment model studied here.61.69% of hypertensive patients reported adherence to the prescribed pharmacological treatment.Discussion:OSA screening is feasible with a questionnaire applicable in daily clinical practice. From the pre-test clinical probability, specific diagnostic methods for the diagnosis of OSA must be started, emphasizing cases of resistant AHT, nocturnal AHT, andmasked AHT. Local studies should be carried out to help us understand the causes of non-adherence to antihypertensive drugs in a significant fraction of individuals with AHT

Uso de psicofármacos y riesgo de apnea del sueño en pacientes internados en hospital general / Psychotropic drugs and obstructive sleep apnea risk use in hospitalized medical patients

RESUMEN: Se realizó un estudio descriptivo observacional, de corte transversal, con el objetivo de identificar la asociación del consumo de psicofármacos y el aumento del riesgo de padecer apnea obstructiva del sueño (A.O.S.), en pacientes internados y bajo tratamiento con psicofármacos en Hospital General (Hospital Pasteur, Montevideo, Uruguay) durante julio-septiembre de 2019. Se aplicó el cuestionario STOP BANG, hallándose riesgo elevado de A.O.S en el 59,4% de la muestra, del cual 75,6% corresponde al sexo masculino y el 24,4% corresponde al sexo femenino. El riesgo elevado para A.O.S fue: 54,3% para pacientes en tratamiento con un solo psicofármaco y 71,4% con dos. El grupo de antipsicóticos fue el que se asoció con mayor frecuencia al riesgo elevado de A.O.S.

SUMMARY A cross-sectional study was conducted with the objective of identifying the link between psychotropic medications and an increased risk of suffering from obstructive sleep apnea (OSA) in patients under treatment with psychotropic medication who were hospitalized in General Hospital (Hospital Pasteur, Montevideo, Uruguay) during the July-September 2019 period. The STOP BANG questionnaire was applied, elevated risk of OSA was found in 59.4% of the sample, of which 75.6% were male, while 24.4% were female. The elevated risk of OSA was: 54.4% for patients under treatment with a single psychotropic medication and 71.4% for patients under treatment with two psychotropic medications. Antipsychotics were the most frequently group of psychotropic drugs linked to an elevated OSA risk.

To assess the risk of obstructive sleep apnea in type 2 diabetes mellitus patients in a tertiary care center in Eastern India

Background: Obstructive sleep apnea (OSA) and type 2 diabetes mellitus have a major health impact because of their high prevalence worldwide. Obesity is a common risk factor for both OSA and type 2 diabetes mellitus in middle-aged persons. Aim: This study was conducted to assess the risk of OSA in type 2 diabetes mellitus patients. Materials and Methods: A cross-sectional study was performed at the tertiary care center of Veer Surendra Sai Institute of Medical Sciences and Research, Burla, Odisha, India. Type 2 diabetic patients were evaluated to assess the risk of OSA using the STOP-BANG sleep apnea questionnaire (consisting of eight questions). Results: Of the 150 type 2 diabetic patients, 53.8% had low risk, 28.6% had intermediate risk, and 17.6% had a severe risk for OSA based on questionnaires. Patients with comorbid conditions like hypertension (odds ratio 1.5) and obesity (odds ratio 1.06) have a high risk of OSA. There was a significant relationship between the type of medication and the risk of developing OSA (P < 0.05) in diabetic patients. The patients taking both insulin and oral drugs have a high-risk OSA as compared to those taking only insulin or only oral drugs. Conclusion: The prevalence of OSA is much higher in diabetics than in the general population, the risk is increasing with comorbid conditions like obesity and hypertension, patients who are receiving both oral hypoglycemic drugs and insulin. The screening of OSA among diabetic patients is necessary to identify those at high risk and manage this problem, which may remain undiagnosed in many patients.

Application of NoSAS score, STOP-BANG Questionnaire and Epworth sleepiness scale in evaluating obstructive sleep apnea risk in patients with respiratory disease / 国际生物医学工程杂志

Objective:To compare the value of NoSAS score, STOP-BANG questionnaire (SBQ) and Epworth Sleepiness Scale (ESS) in assessing the risk of obstructive sleep apnea hypopnea syndrome (OSAHS) in patients with respiratory disease (RD).Methods:The clinical data, NoSAS, SBQ and ESS scores of 190 patients who underwent overnight polysomnography (PSG) were collected. According to the receiver operating characteristic (ROC) curve, with different apnea-hypopnea index (AHI) as the judgment cutoff, the sensitivity, specificity, positive predictive value, negative predictive value, diagnostic odds ratio (DOR) and accuracy of the three scales were compared.Results:With AHI ≥5 times/h as the cutoff, the area under the ROC curve (AUC) of NoSAS and SBQ were 0.833 and 0.729, respectively, indicating that both have predictive value for mild OSAHS. Among them, NoSAS had a larger DOR value (16.150), indicating that NoSAS had the higher accuracy in assessing the risk of mild OSAHS. When AHI>15 times/h was used as the cutoff, the AUC value of NoSAS was 0.704, indicating that it has predictive value for moderate OSAHS. When AHI>30 times/h was used as the cutoff, the AUC value (0.706) and DOR value (6.527) of SBQ were high, indicating that it has predictive value and good accuracy for severe OSAHS. The SBQ is more sensitive than NoSAS and ESS when evaluating patients at high risk for OSAHS ( SBQ≥3). Conclusions:When evaluating the risk of mild and moderate OSAHS in RD patients, NoSAS is better than SBQ and ESS, and when evaluating severe OSAHS, SBQ is better than NoSAS and ESS. In clinical work, appropriate predictive tools should be selected according to the actual situation to assess the risk of OSAHS, so as to formulate and implement early intervention plans based on the assessment results.

Comparison of Stop Bang Questionnaire and Epworth Sleepiness Scale for Screening of Obstructive Sleep Apnoea

Obstructive Sleep Apnoea (OSA) is the most common sleep-related breathing disorder and is associated with significant morbidity. A simple but accurate tool to screen patients for OSA is needed. We wanted to compare STOP-BANG Questionnaire & Epworth Sleepiness Scale to predict the probability of OSA. MethodsA prospective observational study of 46 eligible patients was undertaken. They were assessed using SBQ & ESS & stratified as per the risk of OSA. The Apnoea Hypopnea Index (AHI) was calculated & patients were stratified into mild, moderate & severe OSA. The SBQ scores, ESS scores & AHI was then studied along with the predictive probabilities of both questionnaires in diagnosing OSA. ResultsOf the 46 patients, 89.13 % & 45.65 % were classified as high risk on the SBQ & ESS respectively. 78.26 % were diagnosed OSA on the sleep study according to AHI. SBQ had a high sensitivity to predict OSA (97.22 %) & low specificity (40 %). ESS had low sensitivity & high specificity to predict OSA being 52.78 % & 80 % respectively. ConclusionsBoth Stop-Bang questionnaire & ESS help in determining the risk of OSA. STOP-BANG is a better screening parameter due to its high sensitivity & negative predictive value.

Prevalence of Obstructive Sleep Apnea in Surgical Patients Attending at Skims Hospital, Kashmir, and its Correlation with Perioperative Morbidity

Background and Objective: Patients presenting for surgical procedures often get undiagnosed for obstructive sleep apnea(OSA), thus increasing the incidence of perioperative adverse outcomes. Hence, early diagnosis of this disease is importantin formulating anesthetic management and specific means which may decrease the complications and improve outcome,and therefore, the study was conducted to evaluate the prevalence of OSA in patients presenting in our institute for surgicalprocedures.Materials and Methods: A total of 600 patients of aged >18 years, American Society of Anesthesiologists I-III scheduled forelective surgeries under anesthesia, were randomly enrolled in the study. Their demographic data, anthropometric measurementswere noted. They were screened for OSA by STOP-BANG questionnaire and were followed to assess correlation betweenOSA and perioperative morbidity.Results: We observed that out of a total of 600 patients, 23 patients had moderate and severe OSA. Hence, the prevalence ofmoderate-to-severe OSA was 3.8% in our study. Mean age of subjects was 43.1 years and female predominance was seen inthis study. Out of a total of 600 patients, 23 patients had moderate and severe OSA. There was a significant correlation betweenseverity of OSA and anthropometric measurements and perioperative morbidity.Conclusion: Early screening can help in detecting the OSA among patients and thus help in alleviating perioperative morbidity

Observational study to determine the pattern of distribution of stop - bang score in predicting OSA and its implication among female health care providers

Objective: To determine the pattern of distribution of STOP-Bang score in predicting OSA and its implication among female health care providers. Methods: In this study, we enrolled 100 female health care providers with age>20 years and excluded subjects on long term respiratory illness and with secondary cause of obesity. Detailed historyand clinical examination were done along withfilled STOP-Bang questionnaire. Results: We included 100 subjects, the mean age was 26.23 ± 1.74 years, mean BMI was 23.18+ 1.73. Our study results, Snoring, Tiredness and observed apnea were observed more than other parameters. In the study, the significance of snoring (8% with ‘p’ value 0.006), tiredness (52% with ‘p’ value 0.000) and observed apnea (17% with ‘p’ value 0.001) was statistically significant.The most common score on the STOP-Bang questionnaire was 1point (n = 42), followed by no points (n = 41). Subjects with low risk were 57; with high risk were 2 which were statistically significant. Conclusion: Snoring, tiredness and observed apnea play an important factor among females in STOP-Bang score which also was statistically significant.The STOP-Bang questionnaire performed adequately for OSA screening in female health care providersindicated that it could be used as an effective non-invasive screening tool for identifying subjects with high risk of OSA.

Validation of the Japanese Version of the STOP-Bang Test for the Risk Assessment of Obstructive Sleep Apnea Syndrome / 日本プライマリ・ケア連合学会誌

Objective: The objective of this study was to validate the Japanese version of the STOP-Bang test for risk assessment of obstructive sleep apnea syndrome (OSAS).Methods: We retrospectively evaluated inpatients who underwent nocturnal pulse oximetry for OSAS screening at the internal medical wards.Results: One hundred and forty-four subjects were included the study, and 57 subjects who had a 3% oxygen desaturation index ≥10/hr underwent polysomnography. Seventeen and 29 subjects were diagnosed with moderate and severe OSAS, respectively. According to the receiver operating characteristic (ROC) curve analysis, the STOP-Bang test had a higher diagnostic value using a cutoff of 30 kg/m2 for BMI than using a cutoff of 35 kg/m2. A STOP-Bang score of 3 or greater had a sensitivity of 95.7% and specificity of 42.9% for detecting moderate-to-severe OSAS.Conclusion: The STOP-Bang test is a simple and useful tool for the risk assessment of OSAS.

Postoperative use of high flow nasal insufflation for obstructive sleep apnea: a case series / 대한마취과학회지

BACKGROUND: Continuous positive airway pressure (CPAP) therapy is the gold standard treatment for obstructive sleep apnea (OSA), although, associated with poor patient compliance. Conversely, high flow, humidified, temperature-regulated nasal insufflation of oxygen or air is well tolerated.CASE: We describe our experience of three patients with known or suspected moderate to severe OSA who were poorly compliant to CPAP therapy and received high flow nasal insufflation (HFNI) postoperatively. None had significant episodes of desaturation (SpO₂ < 95%) and all patients uniformly reported superior comfort levels than with the CPAP therapy. HFNI generates small amounts of positive end-expiratory pharyngeal pressure, increases inspiratory airflow and decreases dead space ventilation. Due to the open system, less difficulty with the patient-mask interface and improved patient comfort is experienced. These factors help prevent hypopnea and lead to enhanced sleep continuity.CONCLUSIONS: HFNI may be a promising alternative to CPAP therapy in the perioperative setting.

Escala de Epwoth y cuestionario de Stop Bang como predictores del síndrome de apneas hipopneas obstructivas del sueño / Epworth Sleepiness Scale and Stop Bang questionnaire as predictors for the obstructive sleep apnea syndrome / Escala de Epworth e questionário PARAR BANG como preditores de hipopnéias apneia obstrutiva do sono. Síndrome do sono

Introducción: El SAHOS (Síndrome de Apneas e Hipopneas Obstructivas del Sueño) surge de apneas e hipopneas que generan una hipoxia intermitente. La polisomnografía es el gold standard para su diagnóstico. La Escala de Somnolencia de Epworth (ESS) identifica pacientes con somnolencia diurna. El cuestionario Stop Bang reconoce pacientes con riesgo de SAHOS. El objetivo es describir la sensibilidad y especificidad de la ESS y Stop Bang para el diagnóstico de SAHOS realizado con polisomnografía. Métodos: 125 pacientes completaron la ESS, Stop Bang y realizaron una polisomnografía de noche completa. Se confeccionaron dos grupos: pacientes con IAH < 15, y pacientes con IAH ≥ 15. Se calcularon sensibilidad, especificidad, razón de probabilidades (OR) y curvas ROC para el diagnóstico de SAHOS de la ESS y el Stop Bang. Resultados: La prevalencia del grupo IAH ‹ 15 fue de 36%, y del grupo IAH ≥ 15 fue de 64%. Para la ESS, 71 pacientes presentaron somnolencia diurna, 49,3% con un IAH < 15 y 50,7% con un IAH ≥ 15. Especificidad 77,78%, sensibilidad 55%, área bajo la curva ROC 0,6553. Para el cuestionario Stop Bang, 110 pacientes presentaron alto riesgo para SAHOS, 30% con un IAH < 15 y 70% con IAH ≥ 15. Especificidad 26,67%, sensibilidad 96,25%, área bajo la curva ROC 0,7671. Se enfrentaron ambos cuestionarios y calcularon sus OR: ESS, OR=1,1014 (p=0,038); Stop Bang, OR=8,099 (p=0,002). Conclusiones: La sensibilidad de ESS es baja y su área bajo la curva ROC poco significativa. La gran sensibilidad del cuestionario Stop Bang junto con su área bajo la curva ROC, lo convierten en una herramienta de importancia para realizar screening de SAHOS.

Introduction: osa (obstructive sleep apnea) arises from apneas and hypopneas that cause intermittent hypoxia. Polysomnography is the gold standard for its diagnosis. The Epworth Sleepiness Scale (ESS) measures daytime sleepiness. The Stop Bang Questionnaire (SBQ) recognizes patients at risk of OSA. Objectives: describe the sensitivity and specificity of the ESS and SBQ for the diagnosis of OSA accomplished by polysomnography. Methods: 125 adult patients completed the ESS, SBQ and a full night polysomnography. Patients were grouped into two: those with AHI < 15 and those with AHI ≥ 15. Sensibility, specificity, odds ratio (OR) and ROC curves were determined for the ESS and SBQ. Results: The group with AHI ≥ 15 prevailed (64%). 71 patients (56.8%) showed an abnormal ESS´s score; 49.3% showed an AHI < 15 and 50.7% AHI ≥ 15. The specificity was 77.78% and sensitivity 55%. The area under the ROC curve was 0.6553. Regarding the SBQ, 110 patients were within the high risk group; 30% corresponded to an AHI < 15 and 70% AHI ≥ 15. The specificity was 26.67% and sensitivity 96.25%. The area under the ROC curve was 0.7671. The OR for the ESS was 1.1014 (p=0.038) and SBQ, OR = 8.099 (p=0.002). Conclusion: The sensitivity of the ESS is low and the area under the ROC curve insubstantial. The SBQ shows high sensitivity and a remarkable area under the ROC curve, which turn it into an important tool for screening OSA.

Introdução: sahos (síndrome da apneia e hipopneia obstrutiva do sono) surge de apnéias e hipopnéias que geram hipóxia intermitente. A polissonografia (PSG) é o gold standard para o diagnóstico. A Escala de Sonolência de Epworth (ESS) identifica pacientes com sonolência diurna. O questionário Stop bang reconhece pacientes em risco de doenca de SAHOS. O objetivo de este trabalho é descrever a sensibilidade e especificidade da ESS e do questionario Stop Bang para diagnóstico de SAHOS feito coma PSG. Métodos: 125 pacientes completaram a ess, o stop bang efisseram uma psg con oximetria de noite completa. Dividiram-se os pacientes em dois grupos: com IAH < 15 e 50,7% com um IAH ≥ 15. A especificidade foi de 77,78%, a sensibilidade de 55%, e a área abaixo da curva ROC 0,6553. Enquanto ao questionário stop bang, 110 pacientes apresentaram alto risco de SAHOS, 30% com um IAH < 15 e 70% com IAH ≥ 15. Especificidade de 26,67%, 96,25% de sensibilidade, e 0,7671 da área abaixo da curva. Se comparam ambos questionários e foi calculada sua OR: ESS, OR = 1,1014 (p = 0,038); Stop Bang, OR = 8,099 (p = 0,002). Conclusões: a sensibilidade ess é baixa e a área baixo da curva roc insignificante. A alta sensibilidade do questionário Stop Bang junto com a área baixo da curva ROC o tornam uma ferramenta muito importante para o sreening de esta doença.

Utilidad de los componentes del cuestionario Stop-Bang para identificar pacientes con apneas del sueño / Usefulness of the components of the Stop-Bang questionnaire to identify patients with sleep apnea

Introducción: Los cuestionarios para calcular la probabilidad de padecer apneas del sueño (SAHOS) tienen utilidad variable, por lo que resultaría interesante conocer el desempeño del cuestionario STOP-BANG en nuestra población de alto riesgo usando métodos simplificados de diagnóstico. Objetivo: Evaluar el desempeño de STOP-BANG y su capacidad de predicción para identificar un índice de apneas e hipopneas por hora de registro (IAH) elevado en pacientes con sospecha clínica de apneas del sueño derivados para la realización de una poligrafía respiratoria domiciliaria auto-administrada (PR) de nivel III. Métodos: Estudio longitudinal en pacientes referidos para PR (nivel III) durante catorce meses. Las habilidades de STOP-BANG para discriminar pacientes con SAHOS para cada grado de severidad se validaron contra los resultados de la PR usando el IAH. Se evaluaron la combinación de síntomas (STOP), los parámetros antropométricos (BANG) y STOP-BANG para cada punto de corte propuesto en el IAH manual (>5 y ≥30/hora) y se construyeron modelos de regresión logística múltiple expresando Odds Ratio (OR) con sus intervalos de Confianza (IC) para el 95% para cada uno de los componentes. Se evaluaron en cada modelo el poder de discriminación, calculando el área bajo la curva ROC y la bondad de ajuste mediante la prueba de Hosmer-Lemershow. Resultados: Se estudiaron 299 pacientes. 194 fueron hombres (64.9%), media de 52.77 años (SD: 14.67) e IMC de 32.49 (SD: 7.67). 161 casos (53.8%) presentaron un índice de masa corporal (IMC) >30 (obesos). El desempeño para IAH >5/hora (área bajo la curva ROC) para cada combinación del número de componentes presentes fue; STOP: 0.58, BANG: 0.66 y STOP-BANG: 0.66. La mejor relación sensibilidad (S) y especificidad (E) para la identificación de IAH >5/h se obtuvo con tres componentes de STOP en cualquier combinación posible (S: 52.97%; E: 60%) y con dos componentes de BANG (S: 79%; E: 43.75%). Para un IAH ≥ 30/h el área bajo la curva ROC para cada combinación fue; STOP: 0.67, BANG: 0.67, y STOP-BANG: 0.73 y la mejor relación S-E se obtuvo con dos componentes de STOP (S: 79% - E: 43.75%). De manera similar, 3 componentes de BANG alcanzaron una S de 61.7% y E de 65.48%. Cinco componentes de STOP-BANG (cualquier combinación) alcanzaron una S de 60.73% y E de 65.00% (RV+: 1.73- RV-: 0.60). Finalmente, utilizando selector automático de variables para los ocho componentes de STOP-BANG hallamos un modelo para predecir IAH ≥30/hora formado por; apneas observadas (O): OR: 3.62 (CI 95%: 1.69-7.77) p= 0.001, IMC >30 (B): OR: 2.51 (CI95%: 1.19-5.28) p= 0.015 y sexo masculino (G): OR: 6.63 (CI95%: 2.39-18.3) p= 0.0001 (Área bajo la curva; 0.75. Bondad de ajuste: 0.722). Conclusiones: STOP-BANG muestra un comportamiento diferente para IAH >5 y ≥ 30/ hora cuando se utiliza PR. La combinación STOP muestra escasa capacidad de discriminación para IAH >5/hora y este comportamiento difiere de los resultados publicados con polisomnografía en el laboratorio de sueño. Las variables antropométricas (BANG) muestran buena capacidad de discriminación evaluada por el área bajo la curva del modelo para ambos puntos de corte en el IAH analizados. Cinco componentes de STOP-BANG en cualquier combinación tienen una S diagnóstica elevada para identificar pacientes con alteraciones respiratorias del sueño de grado severo. Mostraron buen desempeño como predictores tres variables antropométricas (IMC, edad y sexo masculino) siendo esta última la de mayor peso para identificar IAH patológico (>5/hora) o elevado severo (≥30/h). En nuestra población el modelo de predicción O-G-B obtuvo el mejor desempeño.

Purpose: The questionnaires used to estimate the probability of suffering from obstructive sleep apnea (OSA) have variable utility. The ability of the STOP-BANG questionnaire has not been evaluated in our high risk population. Aims: The aim of this study was to evaluate the ability of the STOP-BANG assessment tool to predict sleep hourly apnea-hypopnea index (AHI) in patients with high clinical suspicion compared to a self-administered home level III respiratory polygraphy (RP). Methods: We conducted a longitudinal study in patients referred to RP (level III) over fourteen months. The ability of STOP-BANG questionnaire to identify patients with OSA for each severity grade was validated against the results of RP using AHI. The relationships between symptoms (STOP), anthropometrics parameters (BANG) and the combination (STOP-BANG) and AHI (>5 and ≥ 30/hour) were evaluated using multiple logistic regression linear models expressing Odds Ratio (OR) with 95% confidence intervals (CI) for each of the components. For each model, we studied the discrimination power by calculating the area under ROC curve and the fitness using the Hosmer-Lemershow test. Results: 299 patients were studied. 194 were male (64.9%), average age was 52.77 years (SD: 14.67) and body mass index (BMI) was 32.49 (SD: 7.67). 161 cases (53.8%) showed BMI > 30 (obesity). The frequency of identifying AHI >5/hour (area under ROC curve) for each measured component were; STOP: 0.58, BANG: 0.66, and STOP-BANG: 0.66. The best relationship between sensitivity (S) and specificity (Sp) for identifying AHI > 5/h was found by using three STOP components in any possible combination (S: 52.97%; Sp: 60%) with two BANG components (S: 79%; Sp: 43.75%). For an AHI ≥ 30/h the area under ROC curve for each combination were; STOP: 0.67, BANG: 0.67 and STOP-BANG: 0.73. The best relation including S-Sp has been obtained with two STOP components (S: 79%-Sp: 43.75%). Similarly, 3 BANG components reached S of 61% and Sp of 65.48%. Five components of STOP-BANG (in each combination) reached S of 60.73% and Sp of 65.00% (RV+: 1.73 - RV-: 0.60). Finally, we used an automatic selector of variables for the eight STOP-BANG components and we found a model to predict AHI ≥ 30/hour formed by; observed apneas (O): OR: 3.62 (CI 95%: 1.69-7.77); p = 0.001, IMC > 30 (B): OR: 2.51 (CI 95%: 1.19 - 5.28); p = 0.015 and male sex (G): OR: 6.63 (CI 95%: 2.39 -18.3); p = 0.0001 (Area under the curve; 0.75. Goodness of fit). Conclusions: The STOP-BANG questionnaire shows different results for AHI >5 and AHI ≥ 30/hour when RP has been used. The STOP combination shows low capacity to discriminate for AHI > 5/hour and this result differs from the results reported with polisomnography in the sleep laboratory. The anthropometric variables (BANG) show good discriminating capacity evaluated by the area under curve of the model for both cutoff in the analyzed AHI. Five STOP-BANG components in any combination have a high diagnostic sensitivity to identify patients with sleep respiratory disturbance in severe grade. Three anthropometric variables showed good performance as predictors (BMI, age and male sex); the last one was the most important to identify pathologic AHI (> 5/hour) or severe high AHI (≥30/h). In our population the prediction model O-G-B had the best performance.